Abstract
This paper presents an approach for recognizing articulated vehicles in Synthetic Aperture Radar (SAR) images based on invariant properties of the objects. Using SAR scattering center locations and magnitudes as features, the invariance of these features with articulation (e.g. turret rotation of a tank) is shown for SAR signatures of actual vehicles from the MSTAR (Public) data. Although related to geometric hashing, our recognition approach is specifically designed for SAR, taking into account the great azimuthal variation and moderate articulation invariance of SAR signatures. We present a recognition system, using scatterer locations and magnitudes, that achieves excellent results with the real SAR targets in the MSTAR data. The articulation invariant properties of the objects are used to characterize recognition system performance in terms of probability of correct identification as a function of percent invariance with articulation. Results are also presented for occluded articulated objects.
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© 2000 Springer-Verlag Berlin Heidelberg
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Jones, G., Bhanu, B. (2000). Recognition of Articulated Objects in SAR Images. In: Nagel, HH., Perales López, F.J. (eds) Articulated Motion and Deformable Objects. AMDO 2000. Lecture Notes in Computer Science, vol 1899. Springer, Berlin, Heidelberg. https://doi.org/10.1007/10722604_9
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DOI: https://doi.org/10.1007/10722604_9
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-67912-7
Online ISBN: 978-3-540-44591-3
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